Moving Basis Decomposition for Precomputed Light Transport

In this paper, we study the problem of efficient representation of potentially high-dimensional, spatially coherent signals in the context of precomputed light transport. We present a basis decomposition framework, Moving Basis Decomposition (MBD), that generalizes many existing basis expansion methods and enables high-performance, seamless reconstruction of compressed data. We develop an algorithm for solving large-scale MBD problems, evaluate MBD against state-of-the-art in a series of controlled experiments, and describe a real-world application where MBD serves as the backbone of a scalable global illumination system powering multiple, current and upcoming 60Hz AAA-titles running on a wide range of hardware platforms.

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